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. 2022 Dec 19;12(1):21959.
doi: 10.1038/s41598-022-26374-w.

Improvement of a coastal vulnerability index and its application along the Calabria Coastline, Italy

Daniela Pantusa  1 , Felice D'Alessandro  2 , Ferdinando Frega  3 , Antonio Francone  4 , Giuseppe Roberto Tomasicchio  4
Affiliations

Improvement of a coastal vulnerability index and its application along the Calabria Coastline, Italy

Daniela Pantusa et al. Sci Rep. .

Abstract

The present paper further develops a coastal vulnerability index formulation (CVI) previously proposed by the authors by integrating a new variable and redefining three variables to improve the suitability of the index for low-lying coasts. Eleven variables are divided into three typological groups: geological, hydro-physical process and vegetation. The geological variables are: geomorphology, shoreline erosion/accretion rates, coastal slope, emerged beach width, and dune. The hydro-physical process group includes: river discharge, sea-level change, mean significant wave height and mean tide range. The vegetation variables are: vegetation behind the back-beach and coverage of Posidonia oceanica. The index was applied to a stretch of the Ionian coast in the province of Crotone in the Calabria region (Southern Italy), and a vulnerability map was produced. A geography information system (GIS) platform was used to better process the data. For the case study area, the most influential variables are shoreline erosion/accretion rates, coastal slope, emerged beach width, dune, vegetation behind the back-beach, and coverage of Posidonia oceanica. The most vulnerable transects are those near urban areas characterized by the absence of dunes and vegetation. Statistical and sensitivity analyses were performed, and the proposed CVI was compared with the previous formulation proposed by the authors and with two other CVI methods present in the literature.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Figure 1
Figure 1
Case study area. Torretta di Crucoli – Cirò Marina, Calabria region, Italy. The map was created using QGIS 3.29 software (https://qgis.org).
Figure 2
Figure 2
Case study area and related transects. The map was created using QGIS 3.29 software (https://qgis.org).
Figure 3
Figure 3
The scatter plot shows the results of Pearson’s product-moment correlation considering the three groups of variables and the overall CVI value with the correlation coefficient value (r) highlighted.
Figure 4
Figure 4
Score value maps for each variable: (a) geomorphology, (b) coastal slope, (c) shoreline erosion/accretion rates, (d) emerged beach width, (e) dune, (f) river discharge, (g) relative sea-level change, (h) mean significant wave high, (i) mean tide range, (j) vegetation behind the back-beach, (k) coverage of Posidonia oceanica. The map was created using QGIS 3.29 software (https://qgis.org).
Figure 5
Figure 5
CVI category for each transect. The map was created using QGIS 3.29 software (https://qgis.org).
Figure 6
Figure 6
Proposed CVI formulation and previously CVI formulation. The map was created using QGIS 3.29 software (https://qgis.org).
Figure 7
Figure 7
Proposed CVI formulation and CVI formulations proposed by Ružić et al. and Palmer et al.. The map was created using QGIS 3.29 software (https://qgis.org).
See this image and copyright information in PMC

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